Skill UI

A comprehensive guide for deploying web scraping applications powered by Firecrawl to various production environments. Covers Vercel serverless functions, Google Cloud Run, and self-hosted Docker setups. Learn how to configure platform-specific secrets, implement API routes, and handle asynchronous crawl results via webhooks for scalable, reliable production service.

A comprehensive guide for deploying Fireflies.ai integrations into production environments. This skill covers setting up the GraphQL client, implementing secure webhook receivers with signature verification, and managing multi-platform deployments across Vercel, Docker, and Google Cloud Run. Ideal for integrating AI-powered meetings data into production services.

Manages Firebase/Firestore CRUD, queries, batch jobs, and security for applications while extending to A2A agent messaging, MCP server integration, and Cloud Run coordination for advanced workflows.

A comprehensive guide for deploying applications, especially those integrated with AI services like Gamma, to major cloud environments including Vercel, AWS, GCP, and GitHub. Covers best practices for secret management, environment variable configuration, and setting up CI/CD pipelines across various cloud architectures.

Guides building production-ready serverless apps on GCP with Cloud Run services and Functions, covering containerized APIs, event-driven Pub/Sub workflows, cold-start tuning, and deployment automation.

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

Guides GCP users through GCS bucket configuration, offering best practices, configuration patterns, and production-ready snippets whenever someone asks about storage setup within Google Cloud.

Provides automated guidance for Google Cloud Storage lifecycle policy scenarios, including pattern recommendations, production-ready configurations, and best practices for compute, storage, BigQuery, Vertex AI, and other GCP-specific services.

Generates production-ready Terraform, CloudFormation, Pulumi, ARM, or CDK templates via the infrastructure-as-code-generator plugin to automate cloud infrastructure deployment across AWS, Azure, and GCP from user specifications.

Sets up production-grade Genkit infrastructure via Terraform, covering Firebase Functions, Cloud Run, GKE, AI monitoring, and CI/CD wiring so deployments run securely at scale.

A comprehensive guide to building enterprise-grade AI applications using Firebase Genkit. This skill covers the full development lifecycle, including implementing advanced RAG systems, multi-step tool-calling agents, and complex workflows across Node.js, Python, and Go. It teaches best practices for schema validation (Zod/Pydantic), robust error handling, OpenTelemetry tracing, and deploying reliably to Firebase Functions or Cloud Run.

Validates Vertex AI Agent Engine GitHub Actions workflows, enforcing Workload Identity Federation, least-privilege IAM, OIDC permissions, and security scanning so GCP deployments stay automated and secure.